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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Thermal barrier coating life prediction model development

The objective of this program is to establish a methodology to predict Thermal Barrier Coating (TBC) life on gas turbine engine components. The approach involves experimental life measurement coupled with analytical modeling of relevant degradation modes. The coating being studied is a flight qualified two layer system, designated PWA 264, consisting of a nominal ten mil layer of seven percent yttria partially stabilized zirconia plasma deposited over a nominal five mil layer of low pressure plasma deposited NiCoCrAlY. Thermal barrier coating degradation modes being investigated include: thermomechanical fatigue, oxidation, erosion, hot corrosion, and foreign object damage.

Demasi, J. T.↗
DOE OSTI2022

Modeling Predictive Maintenance for NuScale’s Condensate and Feedwater System Using EMRALD

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is used to model of NuScale’s feedwater and condenser system to capture component degradation and repairing process. To model the reliability of the components, a three-stage failure rate is used contrary to a constant rate leading to component failure. Results from EMRALD will be used to compare different maintenance strategies to reduce system downtime. The outcome of the project will assist in maximizing remaining useful life of the overall system and increasing the availability and revenue of the plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

The construction of life prediction models for the design of Stirling engine heater components

The service life of Stirling-engine heater structures of Fe-based high-temperature alloys is predicted using a numerical model based on a linear-damage approach and published test data (engine test data for a Co-based alloy and tensile-test results for both the Co-based and the Fe-based alloys). The operating principle of the automotive Stirling engine is reviewed; the economic and technical factors affecting the choice of heater material are surveyed; the test results are summarized in tables and graphs; the engine environment and automotive duty cycle are characterized; and the modeling procedure is explained. It is found that the statistical scatter of the fatigue properties of the heater components needs to be reduced (by decreasing the porosity of the cast material or employing wrought material in fatigue-prone locations) before the accuracy of life predictions can be improved.

Petrovich, A.↗
DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2002

Model predictions and visualization of the particle flux on the surface of Mars

Model calculations of the particle flux on the surface of Mars due to the Galactic Cosmic Rays (GCR) can provide guidance on radiobiological research and shielding design studies in support of Mars exploration science objectives. Particle flux calculations for protons, helium ions, and heavy ions are reported for solar minimum and solar maximum conditions. These flux calculations include a description of the altitude variations on the Martian surface using the data obtained by the Mars Global Surveyor (MGS) mission with its Mars Orbiter Laser Altimeter (MOLA) instrument. These particle flux calculations are then used to estimate the average particle hits per cell at various organ depths of a human body in a conceptual shelter vehicle. The estimated particle hits by protons for an average location at skin depth on the Martian surface are about 10 to 100 particle-hits/cell/year and the particle hits by heavy ions are estimated to be 0.001 to 0.01 particle-hits/cell/year.

NASA Center JSC↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Lag Model Prediction of the NASA Juncture Flow

The Juncture Flow Experiment is a new validation class experiment that is simulated here using the Lag turbulence models. The genesis of this experiment was the anomalous side of body separations seen in solutions in Drag Prediction Workshop flowfields. Even the simplest Lag model, the eddy-viscosity version, appears to be quite capable of giving reasonable predictions of this flowfield. With sufficient grid resolution and no internal grid singularities, a very fast and localized oscillation occurs in the wing tip trailing edge region. The predictions for the side of body separation are improved with the enhanced grid system.

Michael E Olsen↗
NASA NTRS2014

NASA AVOSS Fast-Time Wake Prediction Models: User's Guide

The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.

Ahmad, Nash'at N.↗
NASA NTRS1984

Rotary balance data for a typical single-engine general aviation design for an angle-of-attack range of 20 to 90 deg. 3: Influence of control deflection on predicted model D spin modes

The influence of control deflections on the rotational flow aerodynamics and on predicted spin modes is discussed for a 1/6-scale general aviation airplane model. The model was tested for various control settings at both zero and ten degree sideslip angles. Data were measured, using a rotary balance, over an angle-of-attack range of 30 deg to 90 deg, and for clockwise and counter-clockwise rotations covering an omegab/2V range of 0 to 0.5.

Ralston, J. N.↗
NASA NTRS1992

Comparison of Echo 7 field line length measurements to magnetospheric model predictions

The Echo 7 sounding rocket experiment injected electron beams on central tail field lines near L = 6.5. Numerous injections returned to the payload as 'conjugate echoes' after mirroring in the southern hemisphere. Field line lengths calculated from measured conjugate echo bounce times and energies are compared to predictions made by integrating electron trajectories through various magnetospheric models. Although Kp at launch was 3-, quiet time magnetic models best fit the echo measurements. Geosynchronous satellite magnetometer measurements near the Echo 7 field lines during the flight were best modeled by the Olson-Pfitzer Dynamic Model and the Tsyganenko-Usmanov model for Kp = 3. The discrepancy between the models that best fit the Echo 7 data and those that fit the satellite data was most likely due to uncertainties in the small-scale configuration of the magnetospheric models. The field line length measured by the conjugate echoes showed some temporal variation in the magnetic field, also indicated by the satellite magnetometers. This demonstrates the utility an Echo-style experiment could have in substorm studies.

Nemzek, R. J.↗
NASA NTRS1993

Radiation model predictions and validation using LDEF satellite data

Predictions and comparisons with the radiation dose measurements on Long Duration Exposure Facility (LDEF) by thermoluminescent dosimeters were made to evaluate the accuracy of models currently used in defining the ionizing radiation environment for low Earth orbit missions. The calculations include a detailed simulation of the radiation exposure (altitude and solar cycle variations, directional dependence) and shielding effects (three-dimensional LDEF geometry model) so that differences in the predicted and observed doses can be attributed to environment model uncertainties. The LDEF dose data are utilized to assess the accuracy of models describing the trapped proton flux, the trapped proton directionality, and the trapped electron flux.

Armstrong, T. W.↗
NASA NTRS1995

Grayscale/resolution trade-off for text: Model predictions and psychophysical results for letter confusion and letter discrimination

In a series of papers presented in 1994, we examined the grayscale/resolution trade-off for natural images displayed on devices with discrete pixellation, such as AMLCD's. In the present paper we extend this study by examining the grayscale/resolution trade-off for text images on discrete-pixel displays. Halftoning in printing is an example of the grayscale/resolution trade-off. In printing, spatial resolution is sacrificed to produce grayscale. Another example of this trade-off is the inherent low-pass spatial filter of a CRT, caused by the point-spread function of the electron beam in the phosphor layer. On a CRT, sharp image edges are blurred by this inherent low-pass filtering, and the block noise created by spatial quantization is greatly reduced. A third example of this trade-off is text anti-aliasing, where grayscale is used to improve letter shape, size and location when rendered at a low spatial resolution. There are additional implications for display system design from the grayscale/resolution trade-off. For example, reduced grayscale can reduce system costs by requiring less complexity in the framestore, allowing the use of lower cost drivers, potentially increasing data transfer rates in the image subsystem, and simplifying the manufacturing processes that are used to construct the active matrix for AMLCD (active-matrix liquid-crystal display) or AMTFEL (active-matrix thin-film electroluminescent) devices. Therefore, the study of these trade-offs is important for display designers and manufacturing and systems engineers who wish to create the highest performance, lowest cost device possible. Our strategy for investigating this trade-off is to generate a set of simple test images, manipulate grayscale and resolution, predict discrimination performance using the ViDEOS(Sarnoff) Human Vision Model, conduct an empirical study of discrimination using psychophysical procedures, and verify the computational results using the psychophysical results.

Gille, Jennifer↗
NASA NTRS1998

Comparison of Contamination Model Predictions to LDEF Surface Measurements

Contaminant deposition measurements have been made on species content and depth profiles on three experiments trays from the Long Duration Exposure Facility (LDEF), Auger, Argon sputtering, Electron Spectroscopy for Chemical Analysis (ESCA) and Scanning Electron Microscopy (SEM) analysis. The integrated spacecraft environment model (ISEM) was used to predict the deposition levels of the contaminants measured on the three trays. The details of the modeling and assumptions used are presented along with the predictions for the deposition on select surfaces on the trays. These are compared to the measured results. The trays represent surfaces that have a high atomic oxygen flux, and intermediate oxygen flux, and no oxygen flux. All surfaces received significant solar Ultraviolet flux. It appears that the atomic oxygen was the primary agent that caused significant deposition to occur. Surfaces that saw significant contaminant flux solar UV and no atomic oxygen did not show any appreciable levels of observable deposition. The implications of the atom ic oxygen interaction with contaminant deposits containing silicon contaminant sources is discussed. The primary contaminant sources are DC61104 adhesive and Z306 paint. The results and interpretation of the findings have a potential significant impact on spacecraft surfaces that are exposed to solar UV and atomic oxygen in low Earth orbit.

Gordon, Tim↗
NASA NTRS2014

Uncertainty in Model Predictions of Vibrio Vulnificus Response to Climate Variability and Change: A Chesapeake Bay Case Study

The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4 C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.

model predictions↗
DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Biological Response Models: Predicting Injury and Mortality of Fish During Downstream Passage through Hydropower Facilities

This report describes the U.S. Department of Energy’s HydroPASSAGE project efforts to develop and collect biological response models for integration into the Biological Performance Assessment (BioPA) toolset and the Hydropower Biological Evaluation Toolset (HBET). These models help understand how fish are likely to respond during dam passage when exposed to hydraulic and physical stressors associated with turbines and other hydropower structures. When fish pass through hydropower facilities, they may encounter several stressors, of which the three most common are collision, rapid decompression, and fluid shear. Specialized equipment has been used to develop 99 biological response models for exposure to blade strike, rapid decompression, or fluid shear. The models were gathered from the literature or developed as part of this effort and include models for 31 different species of fish that have various predicted endpoints (i.e., injury or mortality). Among these models, considerable variation in susceptibility to the stressors has been observed from one species to another, and a species’ susceptibility to one stressor does not necessarily indicate similar susceptibility to another. Although several species have been examined, it is still unclear how many other species, which may have different morphological traits, may respond to these stressors, so further examination of the different species is needed. These models can and have been applied in several different cases, often using the BioPA toolset and HBET, to better understand the potential for injury and mortality that may occur during fish passage at hydropower facilities, including specific applications, such as turbine replacement, the installation of new turbines, or changing operations of currently installed turbines. As hydropower is continually developed to meet the electricity needs of society, tools such as HBET and BioPA, used with the integrated biological response models, will aid in the development of technologies and strategies that avoid, minimize, mitigate, or manage environmental effects.

13 HYDRO ENERGY↗
NASA NTRSDate not supplied

Validation of CFD Model Prediction of Flow Boiling Regime Transitions during LN2 Line Chilldown

Propellant storage and transfer during future long-duration missions will involve fuel depot operations in which a donor depot tank is used to fill a receiver spacecraft tank with a cryogenic propellant. Prior to the on-Orbit filling operation both the receiver tank and the transfer line must be cooled. The line chilldown process involves transition between boiling regimes in microgravity that will be quite different from their 1g ground-based counterparts. Since the cryogenic propellant itself will be used to perform the chilldown process, the time constants to cool the wall and the amount of fuel that will be used become important design considerations. In this light, the focus of the present work is to understand the flow boiling characteristics of a cryogenic fluid, namely, liquid nitrogen, during the chill-down of a transfer line using CFD modelling and simulations. The cryogenic chill-down process involves different flow boiling regimes: film boiling, transition boiling and nucleate boiling. The prediction of transition between these regimes in a CFD framework is new and challenging. The present work addresses this challenge by employing a volume-of-fluid (VOF) based methodology with Lee phase change model to predict the film boiling regime of the chill-down process in ANSYS Fluent®. The transition and nucleate boiling regimes are predicted by incorporating a sub-grid model developed by Craft Tech that accounts for bubble nucleation, growth, shedding frequency, and departure diameter. The sub-grid model is implemented into Fluent via a user-defined function for wall-fluid heat flux calculations. The sub-grid model is similar in formulation to the well-known Rensselaer Polytechnic Institute (RPI) boiling model. The model constants are tested for different operating conditions and designated values are reported. The CFD model is validated against published experimental data for liquid nitrogen chill-down of a heated stainless-steel pipe in 1g. Predicted results showing good agreement of wall temperature, rewetting temperature, and transition between film and nucleate boiling with the experimental measurements are presented and discussed.

Boiling regimes↗
NASA NTRS1994

A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 2: Dependence of absorption and extinction on ice crystal morphology

This study builds upon the microphysical modeling described in Part 1 by deriving formulations for the extinction and absorption coefficients in terms of the size distribution parameters predicted from the micro-physical model. The optical depth and single scatter albedo of a cirrus cloud can then be determined, which, along with the asymmetry parameter, are the input parameters needed by cloud radiation models. Through the use of anomalous diffraction theory, analytical expressions were developed describing the absorption and extinction coefficients and the single scatter albedo as functions of size distribution parameters, ice crystal shapes (or habits), wavelength, and refractive index. The extinction coefficient was formulated in terms of the projected area of the size distribution, while the absorption coefficient was formulated in terms of both the projected area and mass of the size distribution. These properties were formulated as explicit functions of ice crystal geometry and were not based on an 'effective radius.' Based on simulations of the second cirrus case study described in Part 1, absorption coefficients predicted in the near infrared for hexagonal columns and rosettes were up to 47% and 71% lower, respectively, than absorption coefficients predicted by using equivalent area spheres. This resulted in single scatter albedos in the near-infrared that were considerably greater than those predicted by the equivalent area sphere method. Reflectances in this region should therefore be underestimated using the equivalent area sphere approach. Cloud optical depth was found to depend on ice crystal habit. When the simulated cirrus cloud contained only bullet rosettes, the optical depth was 142% greater than when the cloud contained only hexagonal columns. This increase produced a doubling in cloud albedo. In the near-infrared (IR), the single scatter albedo also exhibited a significant dependence on ice crystal habit. More research is needed on the geometrical properties of ice crystals before the influence of ice crystal shape on cirrus radiative properties can be adequately understood. This study provides a way of coupling the radiative properties of absorption, extinction, and single scatter albedo to the microphysical properties of cirrus clouds. The dependence of extinction and absorption on ice crystal shape was not just due to geometrical differences between crystal types, but was also due to the effect these differences had on the evolution of ice particle size spectra. The ice particle growth model in Part 1 and the radiative properties treated here are based on analytical formulations, and thus represent a computationally efficient means of modeling the microphysical and radiative properties of cirrus clouds.

Mitchell, David L.↗